The 30 Years Of Shifting In Indonesian Cardiovascular Burden -Analysis Of Global Burden Of Disease Study

doi:10.21203/rs.3.rs-3547014/v1

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Research Article

The 30 Years Of Shifting In Indonesian Cardiovascular Burden -Analysis Of Global Burden Of Disease Study

https://doi.org/10.21203/rs.3.rs-3547014/v1

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Journal Publication

published 07 Feb, 2024

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Importance: Cardiovascular disease (CVD) remains the leading cause of mortality and morbidity. Compared with disease burden rates in 1990, significant reductions in Disability-Adjusted Life Years (DALYs) burden rates for CVD have been recorded. However, general DALYs rates have not changed in Indonesia in the past 30 years. Thus, assessing Indonesian CVD burdens will be an essential first step in determining primary disease interventions.

Objective: To determine the national and province-level burden of CVD from 1990 to 2016 in China.

Design, Setting, and Participants: This research used Global Burden Disease (GBD) 2019 Institute of Health Metrics (IHME) data to analyze CVD burden trends, including mortality, morbidity, and prevalence characteristics of 12 underlying CVDs.

Exposures: Residence in Indonesia

Main Outcomes and Measures: Mortality, Incidence, prevalence, death, and DALYs of CVD.

Results: CVD Deaths have doubled from 278 million in 1990 to 651 million in 2019. ALL CVDs recorded increased death rates, except for rheumatic heart disease (RHD) (-69%) and congenital heart disease (CHD) (-37%). Based on underlying diseases, stroke and ischemic heart disease (IHD) are still the leading causes of mortality and morbidity in Indonesia, whereas stroke and peripheral artery disease (PAD) are the most prevalent CVDs. Indonesia has the second worst CVD DALYs rates compared to ASEAN countries after Laos. At provincial levels, the highest CVD DALY rates were recorded in Bangka-Belitung, South Kalimantan, and Yogyakarta. In terms of DALYs rate changes, they were recorded in West Nusa Tenggara (24%), South Kalimantan (18%), and Central Java (11%). Regarding sex, only RHD and PAD burdens were dominated by females.

Conclusions: CVD mortality, morbidity, and prevalence rates increased in Indonesia from 1990-2019. Importantly, these data could provide reference points for policymakers, such as improving risk factor prevention and health care optimization.

cardiovascular disease

preventable death

DALY

Global Burden of Disease

Questions

What is the trend and burden of cardiovascular disease (CVD) in Indonesia and all its provinces from 1990 to 2019, especially in the context of Disability-Adjusted Life Years (DALYs), and how does this data inform healthcare policy and intervention?

Findings

Indonesia has the second worst CVD DALY rates in the ASEAN region, trailing only Laos.
All categories of CVDs have recorded an increase in death and DALY rates, except for rheumatic heart disease (RHD) and congenital heart disease (CHD).
Stroke and ischemic heart disease (IHD) are the leading causes of CVD-related mortality and morbidity in Indonesia.

Meaning

The increasing burden of CVD in Indonesia is alarming and requires immediate attention from policymakers and healthcare providers.

There is a pressing need for targeted interventions, particularly for high-burden diseases like stroke and IHD, to improve Indonesia's CVD landscape and overall public health.

Cardiovascular Disease (CVD) remains the leading cause of mortality and morbidity worldwide. According to 2019 World Health Organization (WHO) statistics, CVD accounted for approximately 17.9 million deaths, representing 32%. CVD is also responsible for significant disability and deteriorating quality of life in affected persons, with a comparatively more substantial burden in low and middle-income countries[1–4]. As the fourth largest nation by population, Indonesia was severely impacted by the increase in population aging, urbanization, and change in lifestyle. Previous national Studies show CVD caused by stroke and ischemic heart disease as major causes and burden at national level.[5]

The Global Burden Disease (GBD) study is a collaborative multi-national research study that estimates the burden of multiple diseases and their contributing risk factors at the global, regional, and national levels. Research that analyses the burden of cardiovascular disease has been conducted globally. However, specific analysis assessing the CVD burden at the national level, particularly in Southeast Asia, needs to be more comprehensive. The recent GBD 2019 study revealed that Indonesia was the 6th country with the highest number of CVD deaths worldwide in 2019, with an estimated 375,479 deaths. Furthermore, CVD was responsible for the most sizeable DALY (Disability-Adjusted Life Years) compared to other diseases in Indonesia, accounting for 12,4% of total DALYs in the country[3, 6, 7]

Using data from 1990 to 2019, this study analyses the trends in CVD's overall burden (incidence, prevalence, morbidity, and mortality) and the 11 underlying CVD conditions in Indonesia. This analysis will depict the differential trends in CVD burden across regions/provinces in Indonesia. It will inform provincial health authorities as they prioritize interventions and health services to curb the CVD burden. Its attributable risk factors will also be discussed in more detail.

The 2019 Global Burden of Disease study continuously provides consistent and updated global, regional, and national estimates on the burden of diseases, injuries, and risk factors by integrating all available data.13 Briefly, the 2019 GBD study provides comprehensive and systematic assessments from 1990 to 2019 of age-specific and sex-specific mortality and years of life lost (YLLs) for 264 causes, prevalence, and years lived with disability (YLDs) for 328 diseases and injuries, and 84 risk factors in 204 countries and territories. Subnational evaluations in some countries have been introduced since the 2013 GBD study. The GBD study has continuously provided subnational analysis for 12 countries. Including Indonesia.[3, 6, 8, 9]

The general methodology of GBD 2019 and its improvements over previous iterations are described elsewhere (insert ref). The fatal and non-fatal estimates can be obtained from https://vizhub.healthdata.org/gbd-compare/ and http://ghdx.healthdata.org/gbd-results-tool.

Indonesia ‘s GBD Data sources

The data used to calculate the estimated burden in Indonesia can be seen using the “GBD Input Source Tools”. The complete data sources list that informed Indonesia GBD estimates can be found at: Global Burden of Disease Study 2019 (GBD 2019) Data Input Sources Tool | GHDx (healthdata.org).[7] Age- and sex-specific population counts were obtained from the Indonesia Population and Housing Census (1961–2010). Primary data sources for Cause of Death were obtained from the Basic Health Research surveys, Cause of Death Survey, Mortality Registration System Strengthening Project, and Indonesia Sample Registration Systems. GBD Data Input sources ranged from 2011 to 2018. Data from new rounds of important nationwide surveys, such as the Fifth National Health Service Survey21 and the Chronic Disease and Risk Factor Surveillance System22 from 2013 to 2014, were also updated in the 2019 GBD study.

Disease and measurements

We analyzed 11 diseases in CVD categories by GBD. We also add congenital heart disease as an addition, due to treatment for congenital heart disease in Indonesia being a collaboration between pediatric cardiac consultants and interventional pediatric cardiologists. Finally, we included 12 diseases related to heart disease, including aortic aneurysm, atrial fibrillation and flutter (AF), cardiomyopathy and myocarditis, congenital heart anomaly, endocarditis, hypertensive heart disease, ischemic heart disease (IHD), non-rheumatic valvular heart disease, other cardiovascular and circulatory diseases, peripheral artery disease (PAD), rheumatic heart disease (RHD), and stroke. Due to the addition of congenital data, we recalculated the data aggregation for total cardiovascular disease. This causes the data on Cardiovascular disease in this paper and in the GBD tools to have differences. All Cardiovascular disease in this paper includes congenital heart disease in the calculation unless stated differently later.[3, 6, 8, 9]

To generate estimates of morbidity (incidence and prevalence) and mortality, the GBD collaborative uses three standardized modeling tools, including the Cause of Death Ensemble model (CODEm), DisMod-MR, and the spatiotemporal Gaussian process regression (ST-GPR). The CODEm is a well-structured framework that combines different modeling approaches to analyze cause of death data accounting for rates or cause fractions and covariates. The DisMod-MR tool uses a Bayesian meta-regression framework that exploits the relationship between disease epidemiological parameters such as incidence, prevalence, remission, and mortality to generate plausible and consistent estimates from the available data. The data used a 95% Range Uncertainty Interval (UI). DALYs are computed by summing years lived with disability (YLD) and years of life lost (YLL) to premature death. YLDs are the product of disease prevalence and a disability weight for the specific disease sequelae. At the same time, YLLs are derived from the development of a number of deaths and the remaining years expected to live at that age using a standard life expectancy. Further details of GBD analytical methods have been reported elsewhere (add references)

Statistical Analysis

The primary measure used for the statistical analysis was the Estimated Annual Percentage Change (EAPC). The EAPC was calculated for each step of cardiovascular disease in every location for both genders in the dataset. The purpose was to quantify the temporal trends and observe how these measures changed annually over a specified interval.[10]

For each unique combination of cause, measure, and location, EAPC was calculated. The rate for each cause, measure, and location was logarithmically transformed to linearise the trend over time. A simple linear regression model of the form `y = α + βx + ε` was fitted to the transformed data, where `y` is the natural logarithm of the rate, `x` is the calendar year, `α` and `β` are the parameters estimated, and `ε` is the error term. The EAPC was calculated as `EAPC = 100*(exp(β)-1)`, representing the average annual percentage change in the disease rate. [10] All statistical analyses were performed using R.

Burden Change at National Level

1. Deaths

All-age CVD deaths more than doubled from 292 thousand (95% UI: 246 to 339 thousand) in 1990 and increased to 659 thousand (95% UI: 542 to 747 thousand) in 2019. Based on underlying diseases, stroke, and IHD they remained the leading causes of CVD death in Indonesia, comprising 331 thousand (95% UI: 282 to 367 thousand) and 245 thousand (95% UI: 207 to 276 thousand) deaths, respectively, in 2019. However, the most substantial changes were observed for PAD, atrial fibrillation or flutter, and aortic aneurysm, with nearly 3-fold differences in the period. Furthermore, over 30 years, all 12 CVD death causes steadily increased concerning mortality numbers and rates, except for RHD and CHD, with 49% and 44% changes in CVD deaths (Table 1). Age-standardized CVD mortality rates in Indonesia exhibited a gradual increase (11.7%) from 346.7/100,000 population (95% UI: 293.2–398.3) in 1990 to 387.2/100,000 people (95% UI: 321.1–431.9) in 2019.

Table 1

All-age death numbers and age-standardized death rates for selected cardiovascular disease subcategories and percentage changes by sex in Indonesia (1990–2019) --
Disease Sub-Category	All-Age Deaths, No. in Thousands (95% UI)			Age-Standardized Deaths Rate (95% UI) per 100 000
Disease Sub-Category	1990	2019	Change	1990	2019	Change
Cardiovascular diseases
Both	292 (246–339)	659 (542–747)	126%	346.7 (293.2–398.3)	387.2 (321.1–431.9)	11.7%
Female	150 (122–181)	318 (252–379)	112%	345.2 (280.9–414.3)	357.5 (286.6–420.4)	3.6%
Male	142 (114–172)	342 (262–422)	140%	346.5 (282.6–410.1)	416.8 (326.9–497.1)	20.3%
Aortic aneurysm
Both	0.89 (0.72–1.16)	2.77 (2.01–3.88)	212%	1.16 (0.94–1.50)	1.67 (1.23–2.32)	43.8%
Female	0.35 (0.26–0.57)	0.97 (0.71–1.53)	178%	0.89 (0.66–1.36)	1.10 (0.82–1.73)	24.6%
Male	0.54 (0.40–0.76)	1.81 (1.13–2.63)	235%	1.48 (1.08–2.09)	2.38 (1.52–3.43)	61.1%
Atrial fibrillation and flutter
Both	1.51 (1.25–1.83)	4.99 (3.90–6.56)	230%	2.82 (2.33–3.39)	4.33 (3.37–5.65)	53.5%
Female	0.98 (0.76–1.22)	3.08 (2.36–4.29)	216%	3.26 (2.52–3.99)	4.58 (3.49–6.38)	40.7%
Male	0.54 (0.41–0.68)	1.91 (1.38–2.47)	256%	2.25 (1.72–2.84)	3.95 (2.88–5.10)	75.6%
Cardiomyopathy and myocarditis
Both	3.34 (2.61–5.05)	7.46 (5.43–10.30)	123%	3.81 (3.02–5.12)	4.57 (3.13–5.96)	19.9%
Female	1.55 (1.01–2.55)	2.98 (1.91–4.30)	92%	3.53 (2.23–5.32)	3.63 (2.15–5.26)	3.0%
Male	1.79 (1.38–2.93)	4.48 (2.92–6.96)	150%	4.06 (3.16–5.96)	5.64 (3.87–7.53)	39.1%
Congenital heart anomalies
Both	14.02 (6.71–23.83)	7.81 (5.93–10.22)	-44%	6.21 (2.99–10.53)	3.89 (2.92–5.12)	-37.4%
Female	6.18 (2.66–11.44)	3.38 (2.47–4.53)	-45%	5.61 (2.45–10.37)	3.43 (2.47–4.63)	-38.9%
Male	7.84 (3.47–15.97)	4.43 (3.13–6.01)	-43%	6.78 (3.01–13.77)	4.32 (3.00–5.92)	-36.2%
Endocarditis
Both	0.99 (0.71–1.44)	1.88 (1.27–2.84)	90%	0.79 (0.53–1.23)	0.89 (0.61–1.34)	11.8%
Female	0.54 (0.38–0.84)	0.95 (0.59–1.54)	78%	0.83 (0.56–1.33)	0.88 (0.55–1.44)	5.9%
Male	0.45 (0.29–0.80)	0.93 (0.55–1.66)	106%	0.75 (0.46–1.41)	0.89 (0.54–1.56)	17.8%
Hypertensive heart disease
Both	23.67 (14.50–29.63)	50.62 (28.71–61.82)	114%	30.54 (19.40- 38.16)	30.83 (18.44–37.08)	1.0%
Female	13.60 (8.60–18.01)	26.69 (16.03–34.71)	96%	33.62 (21.73–45.55)	30.77 (19.16–39.73)	-8.5%
Male	10.07 (5.38–12.84)	23.93 (11.36–31.87)	138%	26.66 (14.70- 33.24)	30.20 (14.85–38.68)	13.3%
Ischemic heart disease
Both	97.86 (86.02–109.59)	245.34 (207.41–275.67)	151%	118.05 (103.39–132.74)	140.33 (119.78–154.99)	18.9%
Female	45.27 (38.66–53.35)	105.78 (86.28–124.04)	134%	107.24 (91.06–126.78)	118.28 (97.23–136.43)	10.3%
Male	52.59 (44.69–59.69)	139.57 (111.32–170.78)	165%	129.81 (110.47–147.92)	164.83 (133.63–194.18)	27.0%
Non-rheumatic valvular heart disease
Both	0.42 (0.35–0.55)	0.90 (0.68–1.25)	111%	0.50 (0.41–0.62)	0.51 (0.39–0.69)	2.4%
Female	0.23 (0.15–0.30)	0.42 (0.30–0.56)	82%	0.52 (0.35–0.64)	0.46 (0.33–0.60)	-12.0%
Male	0.19 (0.15–0.27)	0.47 (0.30–0.78)	147%	0.47 (0.36–0.65)	0.57 (0.37–0.93)	21.4%
Other cardiovascular and circulatory diseases
Both	2.99 (2.49–3.69)	4.50 (3.64–5.76)	51%	2.90 (2.41–3.71)	2.47 (2.04–3.11)	-14.7%
Female	1.59 (1.31–1.94)	2.26 (1.74–2.76)	42%	2.92 (2.45–3.79)	2.35 (1.81–2.83)	-19.6%
Male	1.40 (1.04–1.99)	2.24 (1.64–3.39)	61%	2.89 (2.13–4.27)	2.62 (1.99–3.82)	-9.4%
Peripheral artery disease
Both	0.09 (0.06–0.11)	0.36 (0.24–0.53)	318%	0.13 (0.10–0.17)	0.25 (0.17–0.36)	90.2%
Female	0.03 (0.02–0.05)	0.11 (0.07–0.18)	274%	0.10 (0.07–0.15)	0.17 (0.11–0.26)	69.8%
Male	0.06 (0.04–0.08)	0.25 (0.14–0.39)	342%	0.17 (0.12–0.24)	0.35 (0.22–0.54)	109.3%
Rheumatic heart disease
Both	2.55 (2.14–2.99)	1.30 (1.11–1.50)	-49%	2.19 (1.80–2.64)	0.67 (0.57–0.76)	-69.4%
Female	1.25 (1.01–1.49)	0.73 (0.60–0.88)	-41%	1.92 (1.57–2.30)	0.72 (0.59–0.85)	-62.7%
Male	1.30 (0.94–1.66)	0.57 (0.45–0.71)	-56%	2.51 (1.78–3.29)	0.61 (0.49–0.74)	-75.7%
Stroke
Both	144.00 (128.32–159.35)	331.35 (282.00–367.07)	130%	177.57 (155.83–198.45)	196.74 (168.45–214.49)	10.8%
Female	78.57 (67.28–89.39)	170.41 (138.97–199.35)	117%	184.78 (155.29–212.70)	191.12 (157.88–220.20)	3.4%
Male	65.43 (56.06–74.71)	160.94 (127.95–194.17)	146%	168.67 (143.65–194.46)	200.41 (163.59–234.70)	18.8%

2. Prevalence and Incidence

All-age CVD prevalence increased by 120%, from 6,968 thousand (95% UI: 5,919–8,174) in 1990 to 15,348 thousand (95% UI: 13,000–18,080) in 2019. Age-standardized prevalence rates (ASPR) increased by 6.1%, from 6,781/100,000 (95% UI: 5,749–7,978) in 1990 to 7,196.3/100,000 (95% UI: 6,089.6–8,495.3) in 2019. Based on sub-categories, stroke and PAD I had the highest prevalence rates, comprising 4,918 thousand (95% UI: 4,417–5,484) with an ASPR of 2,097/100,000 and 3,325 (95% UI: 2,850–3,803) with an ASPR of 1,640/100,000, respectively. This was followed by IHD, which had a prevalence rate of 3,066 thousand (95% UI: 2,621–3,621) with an ASPR of 1,495/100,000. All CVD sub-categories showed increased prevalence rates, except for congenital heart anomalies, with a 3% decrease in prevalence rates per 100,000 population. In terms of the highest changes, endocarditis was recorded at 16%, followed by non-rheumatic valvular heart disease (15%) and cardiomyopathy and myocarditis (13%) (Table 2).

Table 2

All-Age Prevalence and Age-Standardized Prevalence Rates for Selected Cardiovascular Disease (CVD) Subcategories and Their Percentage Change by Sex in Indonesia, 1990–2019
Disease Sub-Category	All-Age Prevalence, No. in Thousands (95% UI)
Disease Sub-Category	1990	2019	Change	1990	2019		Change
Cardiovascular diseases
Both	6,968 (5,919–8,174)	15,348 (13,000–18,080)	120%	6,781.0 (5,749.6- 7,978.8)	7,196.3 (6,089.6- 8,495.3)		6.1%
Female	3,634 (3,087–4,251)	7,984 (6,761–9,391)	120%	6,825.7 (5,789.3–8,010.6)	7,211.8 (6,104.8–8,489.5)		5.7%
Male	3,334 (2,823–3,934)	7,364 (6,223–8,705)	121%	6,727.6 (5,690.4–7,969.8)	7,162.9 (6,045.7–8,509.4)		6.5%
Atrial fibrillation and flutter
Both	653.04 (494.14–841.16)	1,534.66 (1,159.67–1,974.52)	135%	809.06 (611.90–1,036.64)	828.45 (626.16–1,060.05)	2.4%
Female	325.58 (246.68–416.00)	772.41 (581.35–989.08)	137%	769.04 (581.57–983.29)	782.85 (591.24–999.41)	1.8%
Male	327.46 (249.58–420.87)	762.24 (579.38–980.24)	133%	854.55 (646.92–1,096.82)	882.31 (666.82–1,131.08)	3.2%
Cardiomyopathy and myocarditis
Both	23.43 (17.21–31.42)	61.99 (45.54–83.64)	165%	33.11 (24.45–44.04)	37.44 (27.99–49.37)		13.1%
Female	6.82 (4.79–9.32)	18.38 (13.11–25.51)	170%	20.36 (14.50–27.93)	22.84 (16.34–30.69)		12.2%
Male	16.61 (11.93–22.72)	43.61 (31.61–59.89)	162%	47.75 (35.30–63.81)	54.98 (40.78–72.97)		15.1%
Congenital heart anomalies
Both	459.49 (396.25–542.14)	486.32 (417.82–567.00)	6%	216.58 (187.36–254.50)	210.07 (179.13–247.97)		-3.0%
Female	223.41 (192.04–264.97)	241.00 (206.74–281.02)	8%	214.24 (185.05–253.10)	211.82 (181.04–250.23)		-1.1%
Male	236.08 (203.31–279.28)	245.32 (211.94–285.75)	4%	218.62 (189.83–256.50)	208.36 (178.45–245.19)		-4.7%
Endocarditis
Both	3.11 (2.54–3.76)	6.99 (5.68–8.61)	125%	3.17 (2.55–4.03)	3.68 (2.98–4.65)		16.0%
Female	1.65 (1.34–2.01)	3.68 (2.98–4.54)	123%	3.19 (2.56–4.05)	3.66 (2.96–4.61)		14.8%
Male	1.46 (1.20–1.77)	3.31 (2.69–4.09)	127%	3.16 (2.53–4.05)	3.72 (2.99–4.77)		17.6%
Hypertensive heart disease
Both	344.15 (244.75–462.95)	837.61 (596.61–1,138.43)	143%	423.22 (305.14–573.07)	451.86 (322.87–611.03)		6.8%
Female	146.77 (106.84–196.51)	363.60 (260.07–489.18)	148%	350.07 (251.06–471.10)	374.19 (267.62–499.10)		6.9%
Male	197.38 (139.38–269.39)	474.01 (339.15–650.82)	140%	505.32 (361.15–688.91)	542.44 (386.48–744.34)		7.3%
Ischemic heart disease
Both	1,325.71 (1,137.67–1,554.42)	3,065.68 (2,621.07–3,621.20)	131%	1,456.26 (1,247.11–1,698.30)	1,495.01 (1,278.73–1,765.29)		2.7%
Female	476.50 (403.37–565.96)	1,098.88 (926.22–1,319.68)	131%	1,030.01 (871.97–1,221.75)	1,050.65 (883.50–1,252.90)		2.0%
Male	849.21 (731.46–992.01)	1,966.80 (1,687.01–2,312.74)	132%	1,931.08 (1,670.43–2,251.37)	2,000.26 (1,723.72–2,347.10)		3.6%
Non-rheumatic valvular heart disease
Both	48.50 (43.72–53.25)	124.38 (113.10–136.30)	156%	48.09 (43.82–52.39)	55.34 (50.80–60.29)		15.1%
Female	28.12 (25.35–30.95)	69.11 (62.82–75.78)	146%	54.42 (49.53–59.66)	59.80 (54.76–65.30)		9.9%
Male	20.38 (18.20–22.51)	55.26 (49.80–60.75)	171%	41.00 (37.12–45.05)	50.17 (45.75–54.83)		22.4%
Other cardiovascular and circulatory diseases
Both	323.85 (241.33–430.76)	592.16 (444.63–788.22)	83%	214.13 (163.59–278.38)	228.24 (174.37–296.17)		6.6%
Female	165.74 (121.24–225.30)	301.94 (222.71–412.79)	82%	214.53 (161.21–285.62)	225.39 (170.31–300.48)		5.1%
Male	158.11 (117.86–208.85)	290.22 (218.57–377.80)	84%	215.23 (165.11–276.24)	233.97 (180.19–298.70)		8.7%
Peripheral artery disease
Both	1,300.89 (1,110.35–1,490.53)	3,324.59 (2,850.20–3,802.88)	156%	1,461.32 (1,264.64–1,666.71)	1,640.10 (1,423.77–1,870.95)		12.2%
Female	880.57 (753.43–1,007.28)	2,259.94 (1,942.98–2,581.92)	157%	1,889.68 (1,631.38–2,155.94)	2,108.22 (1,825.43–2,408.39)		11.6%
Male	420.32 (357.00–482.13)	1,064.66 (908.04–1,217.20)	153%	974.87 (844.38–1,115.16)	1,089.73 (944.08–1,240.34)		11.8%
Rheumatic heart disease
Both	225.38 (185.58–272.49)	395.03 (328.44–475.61)	75%	135.80 (115.06–159.91)	148.85 (124.74–177.75)		9.6%
Female	126.26 (102.76–153.74)	219.43 (180.28–265.56)	74%	144.25 (121.03–171.57)	163.41 (134.78–197.24)		13.3%
Male	99.12 (82.15–119.29)	175.60 (147.05–209.80)	77%	128.32 (109.98–149.73)	136.31 (115.99–160.94)		6.2%
Stroke
Both	2,260.36 (2,045.21–2,490.94)	4,918.49 (4,417.11–5,483.59)	118%	1,980.22 (1,784.01–2,210.83)	2,097.22 (1,878.06–2,351.78)		5.9%
Female	1,252.80 (1,128.70–1,379.08)	2,635.41 (2,361.29–2,945.46)	110%	2,135.93 (1,919.47–2,376.57)	2,208.94 (1,976.80–2,481.18)		3.4%
Male	1,007.56 (911.21–1,115.23)	2,283.08 (2,047.49–2,546.13)	127%	1,807.75 (1,627.67–2,022.15)	1,960.61 (1,760.43–2,209.14)		8.5%

All-age Incidence increased by 90% from 799 thousand (95% UI: 669–957) in 1990 to 1,521 thousand (95% UI: 1,298-1,786) in 2019. Age-standardized incidence rates increased by 2.8%, from 682,2/100,000 (95% UI: 582.3-800.2) in 1990 to 701.3/100,000 (95% UI: 600.9–821.7) in 2019. Based on sub-categories, stroke had the highest All-age incidence in 2019, with 339.30 thousand (95% UI: 292.60–389.85) incidence. Stroke also had the highest Age-standardized Incidence rate, with 293.33/100.000 (95% UI: 262.25–331.60) in 2019. In terms of the highest changes in Age-standardized Incidence rate, endocarditis was recorded at 30.2%, followed by non-rheumatic valvular heart disease (13.6%) and peripheral artery disease (9.2%) (Table 3).

Table 3. All-Age Incidence and Age-Standardized Incidence Rates for Selected Cardiovascular Disease (CVD) Subcategories and Their Percentage Change by Sex in Indonesia, 1990-2019

Disease Sub-Category	All-Age Incidence, No. in Thousands (95% UI)			Age-Standardized Incidence Rate (95% UI), per 100 000
Disease Sub-Category	1990	2019	Change	1990	2019	Change
Cardiovascular diseases
Both	799 (669-957)	1,521 (1,298-1,786)	90%	682.2 (582.3-800.2)	701.3 (600.9-821.7)	2.8%
Female	404 (340-482)	781 (667-915)	93%	686.1 (586.0-803.6)	703.1 (600.4-823.7)	2.5%
Male	394 (328-476)	740 (629-872)	88%	676.4 (576.0-795.5)	696.2 (595.6-817.6)	2.9%
Atrial fibrillation and flutter
Both	61.25 (46.16-78.70)	142.15 (107.05-182.36)	132%	65.22 (49.53-83.02)	66.74 (50.67-85.21)	2.3%
Female	30.44 (23.03-39.06)	70.35 (52.85-89.97)	131%	62.76 (47.49-80.12)	63.76 (48.21-81.25)	1.6%
Male	30.81 (23.19-39.56)	71.81 (53.80-92.64)	133%	67.83 (51.75-86.32)	69.90 (53.16-89.55)	3.0%
Cardiomyopathy and myocarditis
Both	23.59 (18.78-29.00)	37.93 (30.24-46.67)	61%	15.97 (12.94-19.43)	15.99 (12.95-19.44)	0.1%
Female	9.54 (7.60-11.80)	15.49 (12.39-19.16)	62%	13.02 (10.51-15.96)	13.02 (10.51-15.96)	0.0%
Male	14.05 (11.13-17.32)	22.44 (17.82-27.46)	60%	19.09 (15.56-23.10)	19.09 (15.56-23.10)	0.0%
Congenital heart anomalies
Both	164.01 (122.43-221.37)	121.87 (90.99-165.79)	-26%	71.78 (53.58-96.89)	66.15 (49.39-89.98)	-7.9%
Female	72.71 (54.54-98.25)	56.00 (41.57-75.56)	-23%	65.43 (49.07-88.41)	62.58 (46.46-84.44)	-4.3%
Male	91.31 (68.33-124.02)	65.87 (48.90-89.82)	-28%	77.81 (58.23-105.69)	69.51 (51.60-94.78)	-10.7%
Endocarditis
Both	10.72 (8.57-13.15)	22.62 (18.43-27.10)	111%	7.27 (6.04-8.62)	9.47 (7.89-11.21)	30.2%
Female	5.26 (4.21-6.44)	11.10 (9.02-13.42)	111%	7.02 (5.81-8.32)	9.20 (7.64-10.95)	31.0%
Male	5.46 (4.35-6.70)	11.52 (9.37-13.86)	111%	7.53 (6.27-8.96)	9.73 (8.14-11.57)	29.3%
Hypertensive heart disease
Both	N/A	N/A	N/A	N/A	N/A	N/A
Female	N/A	N/A	N/A	N/A	N/A	N/A
Male	N/A	N/A	N/A	N/A	N/A	N/A
Ischemic heart disease
Both	91.76 (78.23-106.07)	178.37 (155.17-202.47)	94%	97.81 (83.97-112.38)	84.48 (74.16-95.31)	-13.6%
Female	28.68 (24.26-33.38)	49.06 (42.34-55.80)	71%	62.89 (53.35-72.75)	48.11 (41.88-54.94)	-23.5%
Male	63.08 (53.95-72.76)	129.31 (112.49-147.08)	105%	135.94 (117.02-155.98)	124.49 (109.23-140.73)	-8.4%
Non-rheumatic valvular heart disease
Both	3.85 (3.59-4.12)	9.31 (8.65-10.01)	142%	3.15 (2.95-3.37)	3.58 (3.35-3.83)	13.6%
Female	2.18 (2.02-2.34)	4.95 (4.60-5.33)	128%	3.48 (3.25-3.73)	3.78 (3.53-4.05)	8.4%
Male	1.68 (1.55-1.80)	4.36 (4.03-4.70)	160%	2.80 (2.63-3.00)	3.39 (3.17-3.62)	20.9%
Other cardiovascular and circulatory diseases
Both	N/A	N/A	N/A	N/A	N/A	N/A
Female	N/A	N/A	N/A	N/A	N/A	N/A
Male	N/A	N/A	N/A	N/A	N/A	N/A
Peripheral artery disease
Both	136.50 (117.31-156.34)	339.30 (292.60-389.85)	149%	138.61 (120.47-158.01)	151.31 (131.87-172.72)	9.2%
Female	91.58 (78.79-104.88)	226.38 (195.60-260.30)	147%	178.37 (154.67-202.91)	193.64 (167.97-221.52)	8.6%
Male	44.92 (38.53-51.94)	112.92 (97.29-130.20)	151%	95.16 (82.36-108.73)	104.95 (91.12-119.65)	10.3%
Rheumatic heart disease
Both	18.94 (15.27-22.94)	26.62 (21.75-32.05)	41%	10.12 (8.47-11.94)	10.26 (8.34-12.43)	1.4%
Female	10.35 (8.21-12.65)	14.26 (11.44-17.37)	38%	10.49 (8.67-12.53)	11.07 (8.84-13.53)	5.5%
Male	8.59 (7.03-10.37)	12.36 (10.24-14.78)	44%	9.83 (8.32-11.46)	9.57 (7.92-11.43)	-2.6%
Stroke
Both	288.25 (258.30-325.57)	642.94 (573.04-729.35)	123%	272.23 (244.40-306.56)	293.33 (262.25-331.60)	7.8%
Female	153.75 (137.81-173.56)	333.87 (297.00-378.55)	117%	282.63 (253.16-318.85)	297.91 (265.33-337.11)	5.4%
Male	134.50 (120.22-151.90)	309.07 (275.32-351.40)	130%	260.43 (233.86-292.28)	285.59 (255.66-323.18)	9.7%

3. DALYs

The number of DALYs increased by 86% between 1990 and 2019, while DALYs rates/100,000 population remained relatively stable with only a 0.7% decrease. With an age-standardized rate (ASR) of 4.021/100,000, stroke emerged as the leading cause of DALYs, while the DALY ASR for stroke remained unchanged (0%). The second largest contributor was IHD with a DALY ASR of 2,809/ 100,000. The rate of IHD DALYs increased by 10%. Other CVDs with higher DALY rates included PAD (19%), aortic aneurysm (237%), and atrial fibrillation and flutter (18%). The number of DALYs for CVD increased across all age groups except for RHD (Table 4)

Table 4. All-age DALYs numbers and age-standardized DALYs rates for selected cardiovascular disease subcategories and percentage changes by sex in Indonesia, 1990-2019

Disease Sub-Category	All-Age DALYs, No. in Thousands (95% UI)			Age-Standardized DALYs Rate (95% UI) per 100 000
Disease Sub-Category	1990	2019	Change	1990	2019	Change
Cardiovascular diseases
Both	9,257 (7,547–11,181)	17,183 (14,038–19,949)	86%	8,173.3 (6,883.8- 9,534.0)	8,115.7 (6,715.2- 9,254.7)	-0.7%
Female	4,569 (3,631–5,735)	7,719 (6,087–9,435)	69%	7,973.1 (6,509.7–9,656.2)	7,184.5 (5,721.4–8,621.7)	-9.9%
Male	4,687 (3,627–6,056)	9,464 (7,233–11,894)	102%	8,358.8 (6,738.5–10,190.4)	9,060.5 (7,072.8–11,137.6)	8.4%
Aortic aneurysm
Both	21.5 (17.2–28.9)	61.2 (43.1–86.3)	184%	22.0 (17.7–28.9)	30.0 (21.6–42.0)	36.7%
Female	8.1 (5.9–14.2)	19.9 (14.3–32.3)	147%	16.1 (12.0–26.4)	18.9 (13.7–30.4)	17.3%
Male	13.5 (9.6–19.1)	41.3 (25.2–61.0)	206%	28.4 (20.7–40.2)	42.8 (26.7–62.2)	50.9%
Atrial fibrillation and flutter
Both	74.6 (54.8–98.5)	193.0 (143.4–249.1)	159%	96.3 (72.4–126.8)	113.2 (86.6–143.7)	17.5%
Female	40.2 (29.6–52.2)	103.1 (77.6–134.2)	157%	98.8 (74.4–125.9)	112.5 (86.7–144.5)	13.8%
Male	34.4 (24.4–46.9)	89.9 (63.8–119.2)	161%	93.1 (68.3–124.7)	113.5 (84.2–146.6)	21.9%
Cardiomyopathy and myocarditis
Both	121.0 (84.3–226.2)	201.1 (141.7–299.5)	66%	94.0 (72.1–147.2)	93.9 (68.5–130.0)	-0.1%
Female	54.0 (32.0–103.7)	72.0 (46.4–112.0)	33%	82.1 (53.2–142.6)	68.4 (45.2–101.6)	-16.7%
Male	67.0 (47.5–129.4)	129.1 (83.4–210.7)	93%	106.3 (81.9–178.8)	121.5 (83.3–184.3)	14.3%
Congenital heart anomalies
Both	1,224.2 (583.5–2,071.8)	671.6 (508.7–884.2)	-45%	540.1 (258.0–913.0)	338.1 (253.4–450.0)	-37.4%
Female	537.2 (231.9–990.5)	289.2 (208.4–388.3)	-46%	485.4 (210.1–894.5)	297.6 (212.5–401.5)	-38.7%
Male	687.0 (301.5–1,397.5)	382.3 (269.2–520.0)	-44%	592.0 (260.9–1,202.9)	376.4 (260.2–514.2)	-36.4%
Endocarditis
Both	45.9 (35.0–67.0)	67.4 (46.0–100.3)	47%	28.9 (21.3–42.1)	26.7 (18.4–39.3)	-7.6%
Female	25.0 (16.4–40.1)	32.8 (20.2–52.9)	31%	30.6 (21.5–47.6)	26.1 (16.3–42.1)	-14.8%
Male	20.9 (14.6–33.8)	34.6 (20.7–62.5)	65%	27.1 (18.0–46.8)	27.3 (16.6–48.0)	0.5%
Hypertensive heart disease
Both	593.7 (365.6–744.8)	1,162.9 (649.5–1,428.8)	96%	620.5 (396.2–773.4)	575.8 (334.8–693.7)	-7.2%
Female	326.1 (201.5–426.1)	561.1 (326.8–736.3)	72%	661.1 (419.2–863.9)	541.6 (324.3–695.5)	-18.1%
Male	267.6 (143.5–339.7)	601.8 (290.2–807.4)	125%	572.2 (314.2–720.1)	605.5 (308.4–791.1)	5.8%
Ischemic heart disease
Both	2,693 (2,374–3,014)	6,140 (5,129–7,098)	128%	2,553.2 (2,257.0–2,847.3)	2,809.4 (2,379.6–3,182.4)	10.0%
Female	1,169 (1,000–1,371)	2,373 (1,909–2,904)	103%	2,203.8 (1,888.7–2,576.2)	2,179.6 (1,770.9–2,590.8)	-1.1%
Male	1,524 (1,299–1,722)	3,767 (2,998–4,711)	147%	2,922.1 (2,499.8–3,296.9)	3,473.4 (2,800.4–4,241.5)	18.9%
Non-rheumatic valvular heart disease
Both	12.8 (10.2–16.7)	23.7 (18.3–33.1)	85%	11.5 (9.5–14.7)	10.9 (8.6–15.0)	-5.1%
Female	7.0 (4.4–9.5)	10.8 (7.9–14.2)	53%	12.1 (8.0–15.6)	9.7 (12.6–7.2)	-19.8%
Male	5.8 (4.5–8.1)	12.9 (8.4–21.3)	123%	10.9 (8.4–15.1)	12.3 (8.1–19.7)	12.9%
Other cardiovascular and circulatory diseases
Both	140.6 (116.5–171.3)	166.5 (137.1–205.9)	18%	95.2 (80.1–115.9)	70.9 (59.2–86.6)	-25.5%
Female	74.6 (57.7–95.5)	81.4 (65.6–99.2)	9%	98.3 (79.8–119.3)	67.9 (54.7–81.8)	-30.9%
Male	66.0 (51.3–87.9)	85.0 (63.7–121.3)	29%	92.3 (71.2–126.2)	74.4 (56.9–106.2)	-19.5%
Peripheral artery disease
Both	8.5 (4.9–13.8)	23.1 (13.7–36.3)	171%	11.0 (6.2–18.1)	13.0 (7.8–20.5)	18.7%
Female	5.2 (2.7–8.8)	13.0 (6.9–21.9)	150%	12.8 (6.8–22.3)	13.9 (7.6–23.7)	8.0%
Male	3.3 (2.2–5.1)	10.1 (6.4–14.8)	203%	8.7 (22.3–13.4)	11.7 (7.5–17.4)	34.7%
Rheumatic heart disease
Both	124.5 (102.0–144.8)	65.0 (55.1–76.5)	-48%	79.0 (66.9–92.0)	26.1 (22.2–30.5)	-67.0%
Female	66.8 (50.2–81.1)	36.7 (30.3–44.5)	-45%	78.0 (62.9–93.1)	29.0 (24.1–34.9)	-62.8%
Male	57.7 (42.7–73.9)	28.3 (22.9–35.0)	-51%	80.9 (59.0–103.1)	23.2 (18.9–28.4)	-71.4%
Stroke
Both	4,196.4 (3,799.5–4,583.3)	8,407.2 (7,152.1–9,450.9)	100%	4,021.7 (3,626.5–4,414.7)	4,007.6 (3,454.6–4,420.8)	-0.4%
Female	2,256.3 (1,999.5–2,542.5)	4,125.6 (3,373.4–4,895.2)	83%	4,194.0 (3,673.2–4,728.6)	3,819.4 (3,158.0–4,462.4)	-8.9%
Male	1,940.1 (1,686.6–2,193.3)	4,281.7 (3,381.1–5,209.0)	121%	3,824.8 (3,330.6–4,322.1)	4,178.7 (3,401.7–4,978.1)	9.3%

Gender on Cardiovascular Disease Burden

Based on gender, we observed ASPR changes in men (6.5%) and women (5.7%). Stroke had a higher ASPR in women when compared with men (2,208 vs. 1,906/100,000). However, the ASPR for stroke showed higher changes in males when compared with females (8.5% vs. 3.4%). No significant differences in ASPR were recorded for PAD in men (12%) and women (12%). For IHD, ASPR was higher in males (2,000/100,000) when compared with females (1,050/100,000).

However, women and men experienced different changes in the last 30 years, accounting for 3.6% for women and 20.3% for men. Age-standardized CVD mortality rates in men outnumbered women across seven diseases, including stroke, IHD, congenital heart anomalies, cardiomyopathy and myocarditis, endocarditis, aortic aneurysm, and non-rheumatic valvular heart disease.

We observed significant differences in DALYs between genders, with almost all CVDs experiencing increased DALYs in males, except for three CVDs that experienced decreased DALYs in males, including RHD (-71.4%), congenital heart anomalies (-36.4%), and other cardiovascular and circulatory diseases (-19.5%). These data were inversely proportional to DALYs ASRs in females. Only three CVDs showed an increased DALYs ASR: atrial fibrillation and flutter (14%), aortic aneurysm (17%), and PAD (8%).

As shown (Fig. 2), CVD categories exhibited different proportions between males and females. RHD and PAD dominated females, with 57% and 54% age-standardized DALYs rate (ASDR) proportions, respectively. The most significant DALY proportions in males were for aortic aneurysm, cardiomyopathy, myocarditis, and IHD, with 69.4%, 64%, and 61.4% ASDR proportions, respectively. The remaining diseases were slightly different or similar in terms of gender proportions.

Provincial-level burden

The highest age-standardized DALY rate for total CVD was observed in Bangka-Belitung, North Maluku, and South Kalimantan, all more than 10,000 per 100,000 population. During the given period, the ASDR of almost all provinces ranged between 6,000 and 10,000 per 100,000 population, except North Kalimantan, at 4,084 per 100,000 in 2019, representing the province with the lowest DALYs rate in Indonesia. (Table 5)

Table 5. All-age DALYs numbers and age-standardized DALYs rates by province and their percentage changes (1990–2019)

Disease Sub-Category	All-Age DALYs, No. in Thousands (95% UI)				Age-Standardized DALYs Rate (95% UI), per 100 000
Disease Sub-Category	1990	2019	Change	1990		2019	Change
Aceh	182.4 (138.3–240.9)	309.5 (239.5–387.5)	69.7%	9,031.9 (7,240.5–11,147.8)		9,083.1 (7,188.6–10,937.8)	0.6%
Bali	172.3 (138.8–208.1)	262.6 (202.2–327.7)	52.5%	8,680.2 (7,094.2–10,347.4)		6,054.2 (4,684.7–7,499.3)	-30.3%
Bangka-Belitung Islands	57.0 (43.5–73.3)	109.1 (85.6–136.2)	91.4%	11,559.2 (9,166.9–14,313.0)		10,642.4 (8,628.1–12,857.4)	-7.9%
Banten	388.8 (274.5–539.6)	590.2 (447.9–733.7)	51.8%	9,108.0 (7,099.4–11,499.9)		8,807.2 (6,855.8–10,491.2)	-3.3%
Bengkulu	66.9 (49.5–89.7)	121.5 (94.4–149.4)	81.5%	10,197.5 (8,086.2–12,769.2)		8,978.9 (7,212.2–10,689.4)	-12.0%
Central Java	1,432.6 (1,154.5–1,747.1)	2,697.0 (2,116.5–3,241.5)	88.3%	7,270.0 (5,985.4–8,672.9)		7,855.9 (6,212.4–9,352.8)	8.1%
Central Kalimantan	65.0 (48.2–83.4)	132.5 (96.9–170.3)	103.8%	9,955.6 (7,595.9–12,250.7)		8,614.5 (6,490.8–10,569.4)	-13.5%
Central Sulawesi	92.9 (68.3–124.9)	200.0 (154.5–253.1)	115.3%	9,903.6 (7,712.3–12,617.8)		9,260.3 (7,301.5–11,423.1)	-6.5%
East Java	1,761.0 (1,426.9–2,188.9)	3,031.0 (2,435.9–3,657.1)	72.1%	7,414.8 (6,081.9–9,046.3)		7,563.4 (6,123.0–9,046.3)	2.0%
East Kalimantan	74.2 (56.0–96.1)	209.5 (156.8–275.3)	182.4%	9,642.7 (7,753.0–11,887.5)		9,269.6 (7,237.8–11,647.9)	-3.9%
East Nusa Tenggara	173.5 (125.1–239.7)	314.8 (241.2–392.8)	81.5%	7,889.5 (6,116.3–10,166.6)		7,912.7 (6,120.9–9,637.6)	0.3%
Gorontalo	34.4 (25.4–46.9)	79.4 (58.5–103.3)	131.0%	8,159.8 (6,303.2–10,449.6)		8,618.5 (6,414.0–10,874.2)	5.6%
Indonesia	9,256.5 (7,547.4–11,181.5)	17,182.8 (14,038.0–19,948.9)	85.6%	8,173.3 (6,883.8–9,534.0)		8,115.7 (6,715.2–9,254.7)	-0.7%
Jakarta	328.6 (252.7–425.5)	493.6 (371.9–625.8)	50.2%	8,123.0 (6,637.0–9,885.2)		7,486.8 (5,794.1–9,157.7)	-7.8%
Jambi	109.7 (82.6–141.0)	209.6 (162.3–256.9)	91.1%	11,297.2 (8,984.1–13,836.1)		8,859.3 (6,990.5–10,449.0)	-21.6%
Lampung	278.1 (209.5–363.1)	473.6 (368.2–598.6)	70.3%	8,629.1 (6,954.5–10,544.3)		7,572.9 (5,961.3–9,392.5)	-12.2%
Maluku	77.7 (54.0–111.0)	110.5 (84.1–138.7)	42.1%	10,730.1 (8,185.6–14,046.2)		9,570.7 (7,475.3–11,765.7)	-10.8%
North Kalimantan	6.4 (4.0–10.0)	15.8 (11.1–21.9)	147.0%	5,141.7 (3,808.5–7,015.6)		4,084.2 (2,934.9–5,478.8)	-20.6%
North Maluku	48.8 (35.8–66.0)	81.9 (62.5–104.7)	67.8%	12,653.5 (9,958.2–16,150.9)		10,581.8 (8,310.0–12,903.9)	-16.4%
North Sulawesi	103.8 (82.7–130.1)	186.6 (146.0–230.2)	79.7%	8,910.3 (7,169.6–10,935.5)		8,678.7 (6,843.2–10,474.5)	-2.6%
North Sumatra	540.6 (408.2–705.6)	913.8 (709.2–1,158.9)	69.0%	9,237.8 (7,406.0–11,346.1)		8,895.5 (7,077.7–10,885.5)	-3.7%
Papua	53.4 (34.7–78.3)	205.9 (146.7–280.8)	285.8%	10,845.6 (8,299.1–13,743.4)		10,362.8 (7,674.8–13,390.3)	-4.5%
Riau	113.2 (81.2–151.1)	332.4 (245.4–429.1)	193.7%	9,125.6 (7,109.6–11,326.8)		7,816.0 (5,994.3–9,549.5)	-14.4%
Riau Islands	49.2 (36.6–63.9)	71.0 (53.8–89.2)	44.2%	10,150.4 (8,053.0–12,542.6)		7,607.7 (5,926.4–9,168.1)	-25.0%
South Kalimantan	137.5 (94.8–197.7)	324.0 (244.0–415.1)	135.7%	8,994.0 (6,749.1–12,048.9)		10,108.8 (7,838.1–12,629.6)	12.4%
South Sulawesi	316.2 (238.4–425.4)	536.1 (419.1–644.3)	69.5%	7,833.4 (6,169.0–10,010.1)		7,626.2 (6,010.5–8,975.8)	-2.6%
South Sumatra	237.2 (178.4–313.3)	475.5 (367.7–595.7)	100.5%	8,168.6 (6,549.8–10,002.0)		8,096.3 (6,391.1–9,920.8)	-0.9%
Southeast Sulawesi	86.4 (61.4–118.9)	175.5 (134.0–221.6)	103.2%	11,292.5 (8,655.6–14,312.8)		9,945.5 (7,746.7–12,177.4)	-11.9%
West Java	1,412.8 (1,088.6–1,830.9)	3,079.7 (2,404.2–3,792.0)	118.0%	8,150.8 (6,636.2–9,905.0)		8,145.8 (6,445.5–9,810.0)	-0.1%
West Kalimantan	176.7 (132.5–236.4)	282.8 (226.0–346.5)	60.0%	9,817.0 (7,829.4–12,224.5)		8,237.5 (6,782.5–9,729.2)	-16.1%
West Nusa Tenggara	159.5 (100.5–252.5)	325.2 (250.9–397.6)	103.9%	7,364.8 (5,147.8–10,630.0)		8,599.6 (6,809.8–10,259.2)	16.8%
West Papua	24.9 (17.3–34.9)	45.1 (33.1–59.9)	81.0%	9,907.9 (7,636.6–12,487.5)		9,446.1 (7,381.4–11,835.7)	-4.7%
West Sulawesi	56.2 (39.7–78.9)	94.0 (71.6–119.5)	67.1%	12,656.4 (9,698.1–16,281.8)		10,029.0 (7,767.6–12,431.4)	-20.8%
West Sumatra	232.6 (171.8–316.2)	354.0 (277.9–432.7)	52.2%	8,468.3 (6,520.4–11,060.0)		8,174.6 (6,499.1–9,802.2)	-3.5%
Yogyakarta	206.1 (169.6–246.6)	338.9 (281.0–404.2)	64.5%	8,184.0 (6,742.5–9,750.7)		8,132.2 (6,746.5–9,682.9)	-0.6%

The most significant age-standardized DALY rates for total CVDs were recorded in Bangka-Belitung, North Maluku, and South Kalimantan, all equating to > 10,000/100,000 population. During the study period, the ASDR of almost all provinces ranged between 6,000 and 10,000/100,000 population, except North Kalimantan, which experienced 4,084/100,000 people, representing the lowest DALY rates in Indonesia. (Table 5). Following underlying CVDs, stroke, and IHD contributed the most to DALY rates in Indonesia. This domination was also evidenced in all provinces. The stroke had leading DALY rates in almost all provinces, ranging between 29% and 60% of the total CVD DALYs in each province. In contrast, in two provinces on the same island, Central and South Kalimantan, IHD DALYs rates outnumbered stroke DALYs rates by 29% and 6%, respectively. Finally, hypertensive heart disease also should be addressed due to its DALYs rate percentage, which ranges between 6% and 10%.

Between 1990 and 2019, changes in DALY rates varied by province. West Nusa Tenggara (16.8%), South Kalimantan (12.4%), and Central Java (8.1%) had the highest increases in age-standardized DALY rates. East Java and South Kalimantan provinces experienced the most significant rise in age-standardized DALYs rate, with Aortic Aneurysm showing a notable increase of 56.3% and 49.9%, respectively. In comparison, the most significant contributor to the increase in the age-standardized DALYs rate in the province of West Nusa Tenggara was stroke (48.7%)

The three provinces in Indonesia that experienced the highest reduction in the age-standardized DALYs rate for cardiovascular disease were Bali (-30.3%), Riau Islands (-25%), and Jambi (-21.6%). Rheumatic heart disease and congenital heart anomalies were the contributors to these reductions.

Peripheral artery disease was the primary CVD condition that experienced an increase in the age-standardized DALYs rate in every province in Indonesia, with the highest increases observed in Central Kalimantan (27%), East Kalimantan (24%) and East Java (23%). Other cardiovascular diseases that have experienced an increase in the age-standardized DALYs rate in almost every province were atrial fibrillation and flutter and aortic aneurysms.

We observed increased and decreased CVD rates across Indonesian provinces. The three provinces with the highest DALY ASR increases were West Nusa Tenggara (16.8%), South Kalimantan (12.4%), and Central Java (8.1%). East Java and South Kalimantan provinces observed the most notable increments in Age-Standardized DALYs RATE (ASR) linked explicitly to aortic aneurysms, with notable percentages of 56.3% and 49.9%, respectively. On the other hand, stroke (48.7%) emerged as the primary driver behind the notable rise in Age-Standardized DALYs Rate (ASR) in the West Nusa Tenggara province, compared to other factors. The three Indonesian provinces that experienced the highest reduction in DALYs ASR for CVD were Bali (-30.3%), Riau Islands (-25%), and Jambi (-21.6%). RHD and congenital heart anomalies significantly contributed to reduced DALYs ASR.

PAD has experienced increased age-standardized DALY rates in every Indonesian province. The three provinces recording the highest rates were Central Kalimantan (27%), East Kalimantan (24%), and East Java (23%). Other CVDs with increased age-standardized DALY rates in almost every province were atrial fibrillation and flutter and aortic aneurysms.

Comparing Indonesia to Other Southeast Asian

By benchmarking average and trend burdens in Indonesia, we divided the country’s provinces into four quadrants, measuring burden size and providing issue-solving remedies. Quadrants are shown. The lower left quadrant (low burden size with decreased trends) is the ideal quadrant where common burden conditions occur with decreasing trends. The concern lies with provinces in the upper right quadrant, where the burden remains high and is exacerbated by increasing burden trends (Fig. 5)

The shifting CVD burden has been attributed to multiple factors, including economic, behavioral, demographic, health workforce, and health infrastructure factors. In terms of economic factors, the economy has grown over the last 30 years and caused a shift in CVD burden from a lower poorer economy (RHD) to a CVD burden in workers with increased incomes (IHD)^26,27. Regarding behavioral factors, high blood pressure and smoking are standard in Indonesia and are the primary causes of increased DALY rates. Other demographic factors have significant roles - as Indonesia's population ages. It increased NCD risks. Critically, these factors are separate from increased health capacity, resulting in increased NCD burden across provinces.

Risk Factors of Cardiovascular Disease

High systolic blood pressure was the top risk factor for both females and males in both 1990 and 2019, although the DALYs percentage changed slightly over the 30 years. For females, the high body-mass index saw the most significant contribution to DALYs between 1990 and 2019, with a 116% increase. This risk factor saw a massive 169% increase for males over the same period. Air pollution saw a decline in its contribution to DALYs for both genders, with a decrease of 39% for females and 28% for males. There is a dramatic escalation in the significance of high body-mass index. The surge of 116% for females and an even steeper rise of 169% for males is indicative of a growing concern related to obesity and its implications on heart health. This trend might be attributed to lifestyle changes, dietary habits, or societal norms over the past 30 years. Tobacco use as a cardiovascular risk factor displays notable differences between males and females over 30 years. In 1990, tobacco accounted for 13.6% of male DALYs and 4.5% of females. By 2019, the male contribution slightly rose to 13.9%, maintaining its third ranking, whereas for females, it remained relatively stable at 4.6% but dropped to the eighth rank. This data highlights the consistently higher cardiovascular impact of tobacco on males compared to females.

Cardiovascular Disease Trends in Indonesia vs. Global Patterns

Contrary to Global and Asian trends, which reduced both Death and DALY rate of cardiovascular disease, Indonesia's increase in age-standardized death rates for CVD by 11.7%, and stagnant in DALY with only − 0.7% change in 30 years. This positions Indonesia fifth worldwide and first in Southeast Asia for CVD deaths, signaling specific health challenges [11]. [12]. According to an Indonesian Ministry of Health report, CVD imposes the most significant cost burden on national health insurance. Based on 2020 data from the National Health Insurance Report, CVD had the highest annual healthcare costs of all diseases and accounted for approximately IDR 9.8 trillion (655 million USD). Additionally, stroke cost burdens ranked third and generated annual healthcare costs of IDR 2.5 trillion (167 million USD)[13, 14].

Estimates from the Global Burden of Disease (GBD) align with findings from previous studies on the cardiovascular disease (CVD) burden in Indonesia, corroborated by WHO data on non-communicable conditions (NCDs) and reports from regional research from Southeast Asia[15–17]. Indonesia exemplifies the trend observed in lower-middle-income countries, with stroke emerging as the predominant cause of mortality, ahead of ischemic heart disease (IHD) and in a comparison across 192 WHO member countries, stroke mortality rates surpassed those of IHD in 74 countries, and stroke disability-adjusted life years (DALYs) exceeded IHD rates in 62 countries. Notably, a higher incidence of stroke was linked with lower national income levels. Conversely, an increased burden of IHD was associated with higher diabetes mellitus prevalence and elevated mean serum cholesterol levels [18, 19].

Indonesia Pattern in Global Burden Disease

By the rate of prevalence, stroke, and Peripheral arterial disease are Indonesia's two most common CVDs. PAD is frequently neglected, a study of ankle-brachial index examinations in diabetes mellitus patients in Indonesia revealed that 14.5% had lower extremity PAD[20–22]. Another study reported that as many as 42% of chronic kidney disease patients had moderate Ankle Brachial Index (ABI) results. Moreover, according to PAD guidelines, PAD patients can be placed on a severity spectrum, from asymptomatic to severe symptoms, with > 50% of individuals with PAD being generally asymptomatic. These features could mean that PAD becomes a neglected disease in society. In our results, PAD exhibited significant changes across critical parameters, including prevalence, mortality, and morbidity rates. PAD has emerged as an important public health problem, especially in Indonesia, as it ranks first in Southeast Asia regarding most increased age-standardized DALY rates.

CVD Age-Standardized DALYs Rate (ASDR) has remained stagnant for approximately 30 years (-0.7% change). This contrasts with significant CVD ASDR decreases in global and Southeast Asia rates, indicating that Indonesia bears stubbornly high burden rates from increased premature mortality and years of living with disability[23, 24]. Although decreased DALY rates were recorded for RHD and CHD, this was balanced by DALY gains in non-communicable CVD rates. This is also shown by the stagnancy in progress of reducing premature death from Non-communicable Diseases in Indonesia. Several factors have contributed to this stagnancy, including CVD risk factors, primary and secondary prevention measures, socioeconomic status, health infrastructure, and a lack of health workers[25–27].

Gender Difference

Despite an overall rise in mortality and stagnant DALYs, there's a marked gender disparity in these trends. CVD mortality rates have increased by 20.3% in men compared to 3.6% in women, leading to a notable difference (357 vs 416 per 100,000). The reported sex differences in CHD and stroke mortality align with studies showing men generally have higher mortality rates. [24, 28] The findings on sex differences in CVD risk from previous studies have been mixed, with varying results on which gender faces a higher risk. However, in the context of Indonesia, research indicates that men are less likely to seek primary care compared to their female counterparts. This behavioral pattern may contribute to the observed disparities in health outcomes between genders. [29] The lower number of men utilizing primary care services can be attributed to accessibility challenges, particularly for working-age males whose job schedules, predominantly in the morning, conflict with primary care operating hours.

Variation in Provincial Level

Despite the the stagnancies of total DALY, Indonesia has made commendable strides in curbing mortality and morbidity rates associated with congenital heart disease and rheumatic heart disease. This transformation signals a shift from infectious and maternal issues to chronic ailments predominantly observed in the elderly. This evolution can be attributed to enhanced child and maternal healthcare services. Simultaneously, Indonesia is undergoing a demographic transition with an increasing elderly population. Same pattern shown in global and regional[30–34]. This trend is particularly evident in provinces with significant aging populations like West Nusa Tenggara and Central Java. Here, the disease pattern largely mirrors the national trend, with a notable exception for ailments like stroke, ischemic disease, and other chronic CVDs. These particular diseases have substantially increased in these provinces, indicating region-specific health challenges amidst the broader national progress.[35]

Increase in Risk Factor of Cardiovascular Disease

Fail on risk reduction is still the concern in Indonesia, where healthcare fails to make hypertension patients still on the cascade of care, and only 15% of patients with hypertension routinely control to primary healthcare [36–40]. Our study has shown that hypertension is the leading cause of CVD, accounting for 36–42% of all strokes and 20–25% of all IHDs. Additionally, smoking in males led to a large proportion of IHD (25%) and stroke (17%). High blood cholesterol is also a significant risk factor for 17.8%-19% of IHD events and 10% of all ischemic strokes [36, 41–43]. Southeast Asia has one of the highest total cholesterol increases, with four countries implicated: Indonesia, Thailand, Malaysia, and Cambodia. Indonesia is one of the five countries with the highest number of adults with diabetes, accounting for 48% of all diabetes patients in the world [11]. It is also in the top ten countries with the highest number of deaths from high blood sugar[44, 45].

The limitations and recommendations for future research

While our research presents a comprehensive study on the burden of cardiovascular diseases (CVDs) in Indonesia, it is essential to acknowledge its limitations. The study relies heavily on Global Burden of Disease Study data, which, despite being the most comprehensive available, may be subject to inherent biases and inaccuracies due to the absence of a nationwide, reliable data registry for CVD in Indonesia. The study's observational nature did not allow for establishing causative relationships for the shifts in CVD burden. It did not provide predictions for future trends or the impact of interventions.

Given the insights and limitations identified, future research has several directions. A deeper exploration into the underlying causes of the identified trends, especially in provinces like West Nusa Tenggara and Central Java, would be beneficial. Furthermore, there is a need for more comprehensive studies focusing on the gender disparities in CVD mortality and morbidity rates. Investigating the behavioral, socio-economic, and cultural factors contributing to these disparities will provide a richer understanding.

This study highlights Indonesia's unyielding burden of cardiovascular diseases (CVD) over the past 30 years, which contrasts with global and Southeast Asian trends. Notably, stroke is the leading cause of CVD death in Indonesia, and Peripheral Artery Disease, often overlooked, shows worrying trends. We underscore the need for improved prevention, socioeconomic support, and health infrastructure in chronic disease care.

ABI:Ankle Brachial Index;

AF:Atrial Fibrillation and Flutter;

ASDR:Age-Standardized DALYs Rate;

ASPR:Age-Standardized Prevalence Rates;

ASR:Age-Standardized Rate;

CHD:Congenital Heart Disease;

CODEm:Cause of Death Ensemble model;

CVD:Cardiovascular Disease;

DALYs:Disability-Adjusted Life Years;

EAPC:Estimated Annual Percentage Change;

GBD:Global Burden of Disease;

IHD:Ischemic Heart Disease;

NCD:Non-Communicable Diseases;

PAD:Peripheral Artery Disease;

RHD:Rheumatic Heart Disease;

ST-GPR:Spatiotemporal Gaussian Process Regression;

UI:Uncertainty Interval;

WHO:World Health Organization;

YLDs:Years Lived with Disability;

YLLs - Years of Life Lost

Ethics Approval and Consent to Participate

Ethical approval for this study was obtained from Airlangga University. All participants provided informed consent to participate in the study, following the Declaration of Helsinki.

Consent for Publication:

N/A. Identifiable information has been omitted by IHME.

Availability of Data and Materials

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request. Restrictions apply to the availability of these data, which were used under license for this study, and so are not publicly available.

Competing Interests

The authors declare that they have no competing interests.

Funding

The study was conducted with the researcher's funds.

Authors' Contributions

1. F.R. Muharram: Project Leader, Conceptualisation, Data Curation, Formal Analysis, Methodology, Software, Visualisation, Writing - original draft, Project administration.

2. C.e.C.Z. Multazam: Data Curation, Formal Analysis, Methodology, Visualisation, Writing - original draft.

3. A. Mustofa: Data Curation, Formal Analysis, Methodology, Visualisation, Writing - original draft.

4. W. Socha: Data Curation, Formal Analysis, Methodology, Visualisation, Writing - original draft.

5. A. Andrianto: Supervisor, Resource, Data Curation, Data Validation, Funding Acquisition, Investigation, Validation, Writing - Review & Editing.

6. S. Martini: Supervisor, Resource, Data Curation, Data Validation, Funding Acquisition, Investigation, Validation, Writing - Review & Editing, Project administration.

7. L. Aminde: Supervisor, Resource, Data Curation, Data Validation, Funding Acquisition, Investigation, Validation, Writing - Review & Editing, Project administration.

8. C.Y. Li: Supervisor, Resource, Investigation, Validation, Writing - Review & Editing, Project administration.

ACKNOWLEDGEMENTS

We are grateful to the Advanced Research Centre Team, who helped in data curation and analysis.

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No competing interests reported.

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First submitted to journal
02 Nov, 2023

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The 30 Years Of Shifting In Indonesian Cardiovascular Burden -Analysis Of Global Burden Of Disease Study

Status:

Journal Publication

Version 1

Abstract

Figures

KEY POINTS

BACKGROUND

METHODS

Statistical Analysis

RESULTS

DISCUSSION

Cardiovascular Disease Trends in Indonesia vs. Global Patterns

Variation in Provincial Level

CONCLUSIONS

Abbreviations

Declarations

Ethics Approval and Consent to Participate

Consent for Publication:

Availability of Data and Materials

Competing Interests

Funding

Authors' Contributions

ACKNOWLEDGEMENTS

References

Additional Declarations

Status:

Journal Publication

Version 1